In a number of applications, it has become desirable to be able to identify features within a series of images, such as video frames, and track the movement of the features within the images. For example, a series of video frames may be captured that include a distinctive object and it may be desirable to identify and track the relative movement of the object across the video frames and recognize the object in an automated fashion. In this regard, the identification of features within an image is utilized in computer vision applications, such as augmented reality. These applications are being increasingly utilized for real-time object recognition, three-dimensional reconstruction, panorama stitching, robotic mapping, and video tracking.
Handheld devices, such as mobile phones, are now commonly outfitted with video capturing capabilities. These video capturing capabilities can be leveraged for mobile and convenient computer vision applications, such as mobile augmented reality (MAR). However, in at least some instances, the processing power of a handheld device can be a limitation for the image processing capabilities of the handheld device.